A MODEL FOR INTERVAL-CENSORED TUBERCULOSIS OUTBREAK DATA
โ Scribed by PHILIP J. SMITH; THEODORE J. THOMPSON; JOHN A. JEREB
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 254 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0277-6715
No coin nor oath required. For personal study only.
โฆ Synopsis
As the incidence of tuberculosis (TB) has increased in the United States, occupationally acquired TB has increased among the health care workers (HCWs). This paper describes a model developed in response to the needs of an outbreak of multidrug-resistant TB. One of the goals of the outbreak investigation was to estimate the risk of tuberculin skin test (TST) conversion as a function of HCW job type and the period during which persons were employed over the study period. TST conversions were evaluated at periodic examinations and data are interval-censored. We present a generalized linear model that extends Efron's survival model for censored survival data to the case of interval-censored data.
๐ SIMILAR VOLUMES
I create a general model to perform score tests on interval censored data. Special cases of this model are the score tests of Finkelstein, Sun and Fay. Although Sun's was derived as a test for discrete data and Finkelstein's and Fay's tests were derived under a grouped continuous model, by writing a
We derive a non-parametric maximum likelihood estimator for bivariate interval censored data using standard techniques for constrained convex optimization. Our approach extends those taken for univariate interval censored data. We illustrate the estimator with bivariate data from an AIDS study.